The goal of this initiative is to develop a mobile application that provides location-based alerts and advice on healthcare, epidemiology and safety. The proposed Mobile Application for Healthcare, Epidemiology, and Safety (MAES) collects data from multiple sources and data formats; extracts healthcare, epidemiology and safety information; analyzes trends, patterns and geospatial data; forecasts comprehensive, multi-dimensional health and safety statuses; and provides alerts and advice to users. Data collected and analyzed by MAES will include (i) open source unstructured and text data from public health, international and national health organization websites, weather, news feeds and blogs, and (ii) user entered structured and unstructured data (SMS, text, forms, images, and geo referenced data). Natural language processing and advanced data mining techniques will be used to extract information on disease outbreaks, their progression, and their epidemiological analyses. In addition to health and disease outbreaks, MAES will collect, extract and organize information about weather conditions and natural disasters as well as man-made and bioterrorist events. Data mining, machine learning and forecasting algorithms will be used to analyze the data. MAES will use this information to deliver context sensitive, location based alerts, and to provide advice to users on healthcare, diseases, safety and environmental issues.